How to Access Datasets

1. After clicking on the "Data Cloud" heading in the main menu, click on the "Datasets" subheading

2. Click on the desired Dataset from the list

3. Click on Explore Data near the top right

Data Exploration

Data Exploration actions that can be performed in the Datasets view:

• Viewing a 10,000-row display cap for each column present in the dataset with a truncation notice
• Considering the distribution of selected data column results under analysis in the edit column
• Use temporary filters to focus the data view
  • If 2 or more filters are added to the dataset, by default the filters are treated as an AND statement.
  • This can be overridden through the 'Filter Logic' option on the right hand side of the filtering space, which allows for more flexible filtering statements (see below screenshot). This option allows for OR/AND/NOT operations with parenthesis for grouping.
    • Example input: 1 OR 2
    • Example input: (1 OR 2 OR 3) AND 4
      • Where '1,' '2,' '3,' equal the filters that have been added to the dataset.

Data Organization

Data Organization actions that can be performed in the Datasets view:

• Use checkboxes under the "Columns" button near the top left to remove columns from the view
• Use the Edit Column fields to edit the column titles
• Use the Edit Column "Clean Up" section to standardize data results labels with find and replace & capitalization

Data Transformation

Data Transformation actions that can be performed in the Datasets view:

• Create a new data column by combining the results of two different columns
• Create a new data column by extracting a piece of the results of a column into another
• Create a new data column by calculating the results of two other columns

Exploring a SQL Transform Dataset

SQL Transform datasets fully support Explore Data. The experience works the same as with any other dataset type, with a few important distinctions.

How it works

Open a SQL Transform dataset and click Explore Data. The result rows load directly — computed on read — so you can browse the full output without triggering a build or touching the underlying SQL.

Within Explore Data you can:

• Filter the results using the same filter controls available on any dataset
• Sort by any column
• Export to CSV using the export option in the toolbar

Editing the SQL

The SQL editor is no longer accessible directly from the dataset's main view. To modify the underlying query, use the More Actions menu (⋯) and select the edit option. This keeps the browsing and editing experiences separate — Explore Data is for reviewing results, and More Actions is the entry point for making changes.